Browsing by Author "Lin, Shin-Ping"

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A new vehicle detection approach in traffic jam conditions
(2007)
Wu, Bing-Fei
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Juang, Jhy-Hong
;
Tsai, Ping-Tsung
;
Chang, Ming-Wei
;
Fan, Chung-Jui
The well-known vehicle detectors utilize the background extraction methods to segment the moving objects. The back-ground updating concept is applied to overcome the luminance variation which results in the error detection. These systems will meet a challenge when detecting the vehicles in the traffic jam conditions at sunset. The vehicles will cover the road surface so that the background information cannot be smoothly updated. Once the traffic is released, the existing background is not suitable for the moving segmentation. The main contribution of this paper is that an efficient vehicle detection approach is proposed to improve the detection accuracy in traffic jam conditions. The land mask decision gives the land information and the merged boundary box rule is presented to realize vehicle detection. The signed square normalized correlation coefficient calculation is addressed, and it is applied to vehicle tracking. The experimental results show that this approach works well in highway and urban area with high accuracy.
A real-time multiple-vehicle detection and tracldng system with prior occlusion detection and resolution, and prior queue detection and resolution
(2006)
Lin, Shin-Ping
;
Chen, Yuan-Hsin
;
Wu, Bing-Fei
;
電控工程研究所
;
Institute of Electrical and Control Engineering
The proposed multiple-vehicle detection and tracking (MVDT) system utilizes a color background to segment moving objects and exploits relations among the moving objects and existed trajectories to track vehicles. Initially, the background is extracted by classification. Then, it is regularly updated by previous moving objects to guarantee robust segmentation in luminance-change circumstance. For partial wrong converged background due to roadside parking vehicles, it will be corrected later by checking fed back trajectories to avoid false detection after the vehicles moving away. In tracking processing, the relations of distances or distances and angles are applied to determine whether to create, extend, and delete a trajectory. If occlusion detected after trajectory creation, it will be resolved by rule-based tracking reasoning. Otherwise, lane information will be used. In addition, to further resolve occlusion occurred in lane, a queue detection and resolution technique will be utilized prior to tracking processing. Finally, for easy setup, parameter automation for the system is proposed.